Correction of optical device throughput errors using integrated computational elements

ABSTRACT

An optical computing device utilizes an Integrated Computational Element (“ICE”) core to correct calibration transfer errors in the device.

The present application is a U.S. National Stage patent application ofInternational Patent Application No. PCT/US2013/076635, filed on Dec.19, 2013, the benefit of which is claimed and the disclosure of which isincorporated herein by reference in its entirety.

FIELD OF THE DISCLOSURE

Embodiments of present disclosure generally relate to optical devicesand, more particularly, to a multivariate optical computing device thatutilizes Integrated Computational Element (“ICE”) cores to correctdevice throughput errors.

BACKGROUND

ICE cores are variations of multivariate optical elements (“MOE”) whichwere originally targeted for qualitative and quantitative analysis ofphysical or chemical properties of interest in chemometrics. In recentyears, ICE technologies have been developed for various applications,including the Oil and Gas Industry in the form of optical sensors ondownhole or surface equipment to evaluate a variety of fluid properties.ICE cores typically consist of multiple physical layers with differentrefractive indexes in the film material, wherein their optical orspectroscopic characteristics, if designed properly, can be transformedinto effective inputs for linear and nonlinear multivariate calibration.

An optical computing device is a device configured to receive an inputof electromagnetic radiation from a substance or sample of the substanceand produce an output of electromagnetic radiation from a processingelement. The processing element may be, for example, an ICE core.Fundamentally, optical computing devices utilize optical cores toperform regression calculations, as opposed to the hardwired circuits ofconventional electronic processors. When electromagnetic radiationinteracts with a substance, unique physical and chemical informationabout the substance is encoded in the electromagnetic radiation that isreflected from, transmitted through, or radiated from the sample. Thisinformation is often referred to as the substance's spectral“fingerprint.” Thus, the optical computing device, through use of theICE core, is capable of extracting the information of the spectralfingerprint of multiple characteristics or analytes within a substanceand converting that information into a detectable output regarding theoverall properties of a sample.

Optical computing devices are often characterized in terms of each oftheir optical components. The total system throughput can be estimatedas the product of these components, with each component imposing itsindividual effect on the spectral throughput of the device. However, thespectral throughput of compiled optical systems often differ from themodeled spectral throughput due to a number of factors, such as lensaberrations, variation in optical elements, variation in optical elementposition, and other random errors, all of which are not accounted for inthe model. In addition, systematic errors (in which there is a constanterror in the spectral profile) are also unaccounted for in the model. Asa result, the assembled optical computing device will contain throughputerrors which may result in performance degradation in prediction ofsample characteristics.

Accordingly, there is a need in the art for methods by which to correctfor throughput errors in optical systems.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an illustrative ICE core which may be fabricated usingmethods of the present disclosure;

FIG. 2A shows a block diagram of an ICE design system according to anillustrative embodiment of the present disclosure;

FIG. 2B is a flow chart of a illustrative method performed by the ICEdesign system to determine the design of an ICE core to correct acalibration transfer error;

FIG. 3 is a graph of combined and normalized raw spectral data anddevice spectral throughput data utilized to design the ICE core tocorrect the calibration transfer error;

FIG. 4 is a graph showing two examples of simulated calibration transfererror profiles (shown by lines A and B), and the back-calculatedversions of the function (shown by lines C and D) that are based on aFourier transform interpolation of eight points, all generated using theICE design system 200;

FIG. 5 is a block diagram of an illustrative architecture of an opticalcomputing device employing a transmission mode design, which may beutilized in one or more of the optical computing devices of the presentdisclosure; and

FIG. 6 is a block diagram of an illustrative architecture of an opticalcomputing device utilizing a calibration transfer error correctioncircuit, according to certain illustrative embodiments of the presentdisclosure.

DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

Illustrative embodiments and related methods of the present disclosureare described below as they might be employed in an optical computingdevice that self-corrects system throughput errors. In the interest ofclarity, not all features of an actual implementation or method aredescribed in this specification. It will of course be appreciated thatin the development of any such actual embodiment, numerousimplementation-specific decisions must be made to achieve thedevelopers' specific goals, such as compliance with system-related andbusiness-related constraints, which will vary from one implementation toanother. Moreover, it will be appreciated that such a development effortmight be complex and time-consuming, but would nevertheless be a routineundertaking for those of ordinary skill in the art having the benefit ofthis disclosure. Further aspects and advantages of the variousembodiments and related methods of the disclosure will become apparentfrom consideration of the following description and drawings.

As described herein, embodiments of the present disclosure are directedto an optical computing device which utilizes an Integrated ComputationElement (“ICE”) core to correct for system throughput errors, referredto herein as calibration transfer errors (“CTEs”). In a generalizedmethod, the CTE of the optical computing device is determined based uponthe device components. Using the CTE, a correction to the CTE (“CTEcorrection”) is determined and then utilized to design an ICE corehaving the spectral profile necessary to correct for CTEs. In ageneralized embodiment of the present disclosure, the optical computingdevice includes a first ICE core and a second error correcting ICE core.The first ICE core functions to determine the sample characteristic asunderstood in the art. However, the second ICE core acts to correct forCTEs introduced by the device components in a variety of ways. In afirst embodiment, the second ICE core itself corrects theelectromagnetic output of the first ICE core. In a second embodiment, anerror correcting circuit utilizes detector output signals correspondingto the first and second ICE cores to correct for CTEs. In a thirdembodiment, a computer processor analyzes those same detector outputsignals to correct for CTEs. Accordingly, embodiments of the presentdisclosure provide an optical computing device that self-corrects forthroughput errors which were not accounted-for during the designprocess.

As will be described in more detail below, the CTE correcting ICE coreis designed to have a spectral profile (i.e., transmission function)which corrects the CTE. This is achieved, in part, varying the thicknessof the layers forming the CTE correcting ICE core. To generallyillustrate this point, FIG. 1 shows an illustrative ICE core 100 whichmay be fabricated using methods of the present disclosure. ICE core 100may include a plurality of alternating layers 102 and 104, such as, forexample, silicon (Si) and quartz (SiO₂), respectively. Othernon-limiting examples of layer material include niobium, germanium andGermania, MgF, SiO, and other high and low index materials, althoughpersons of ordinary skill in the art having the benefit of thisdisclosure will understand that these layers consist of materials whoseindex of refraction is high and low, respectively.

The layers 102, 104 may be strategically deposited on an opticalsubstrate 106. In some embodiments, the optical substrate 106 is BK-7optical glass. In other embodiments, the optical substrate 106 may beother types of optical substrates, such as quartz, sapphire, silicon,germanium, zinc selenide, zinc sulfide, or various plastics such aspolycarbonate, polymethylmethacrylate PMMA), polyvinylchloride (PVC),diamond, ceramics, etc., as known in the art. At the opposite end (e.g.,opposite the optical substrate 106), the ICE core 100 may include alayer 108 that is generally exposed to the environmental air surroundingthe device or installation. The number of layers 102, 104 and thethickness of each layer 102, 104 may be determined from the spectralattributes acquired from a spectroscopic analysis of a characteristic ofthe sample substance using a conventional spectroscopic instrument.

The spectrum of interest of a given characteristic of a sample typicallyincludes any number of different wavelengths. It should be understoodthat the illustrative ICE core 100 in FIG. 1 does not in fact representany particular characteristic of a given sample, but is provided forpurposes of illustration only. Consequently, the number of layers 102,104 and their relative thicknesses, as shown in FIG. 1, bear nocorrelation to any particular characteristic of a given sample. Nor arethe layers 102, 104 and their relative thicknesses necessarily drawn toscale, and therefore should not be considered to limit the presentdisclosure. Moreover, those skilled in the art will readily recognizethat the materials that make up each layer 102, 104 may vary, dependingon the application, cost of materials, and/or applicability of thematerial to the sample substance. For example, the layers 102, 104 maybe made of, but are not limited to, silicon, quartz, germanium, water,combinations thereof, or other materials of interest. Furthermore, thosesame skilled persons will realize that the physical thicknesses of thelayers 102 are illustrative in nature and, thus, may be altered asdesired.

The multiple layers 102, 104 exhibit different refractive indices. Byproperly selecting the materials of the layers 102, 104 and theirrelative thicknesses and spacing, the illustrative ICE core 100 may beconfigured to selectively pass/reflect/refract predetermined fractionsof light (i.e., electromagnetic radiation) at different wavelengths.Through the use of regression techniques, the corresponding output lightintensity of the ICE core 100 conveys information regarding acharacteristic of the analyte of interest. Moreover, as will bedescribed below, through proper selection of the layer thicknesses, anICE core may be designed to correct for CTEs in the compiled opticalcomputing device.

In view of the foregoing, FIG. 2A shows a block diagram of an ICE designsystem according to an illustrative embodiment of the presentdisclosure. As will be described herein, ICE design system 200 providesa platform for the design of ICE cores which correct for CTEs. FIG. 2Bis a flow chart of an illustrative method 230 performed by ICE designsystem 200 to determine the design of the CTE correcting ICE core. Aswill be described in more detail below, at block 232, ICE design system200 analyzes an optical computing device (assembled or non-assembled) inorder to determine the device throughput errors (i.e., CTE) introducedby the device components. The device components may include, forexample, the lens, beam splitters, or other optical elements along theoptical train. Once determined, at block 234, the system then determinesthe optical spectral profile (regression vector, for example) necessaryto correct for the CTE. Based upon this optical spectral profile, atblock 236, system 200 then determines the design of an ICE core havingthe appropriate spectral profile to correct for the CTE.

Still referring to FIG. 2A, ICE design system 200 includes at least oneprocessor 202, a non-transitory, computer-readable storage 204,transceiver/network communication module 205, optional I/O devices 206,and an optional display 208 (e.g., user interface), all interconnectedvia a system bus 209. In one embodiment, the network communicationmodule 205 is a network interface card and communicates using theEthernet protocol. In other embodiment, the network communication module105 may be another type of communication interface such as a fiber opticinterface and may communicate using a number of different communicationprotocols. Software instructions executable by the processor 202 forimplementing software instructions stored within ICE design module 210in accordance with the illustrative embodiments described herein, may bestored in storage 204 or some other computer-readable medium.

Although not explicitly shown in FIG. 2A, it will be recognized that ICEdesign system 200 may be connected to one or more public (e.g., theInternet) and/or private networks via one or more appropriate networkconnections. It will also be recognized that the software instructionscomprising ICE design module 210 may also be loaded into storage 204from a CD-ROM or other appropriate storage media via wired or wirelessmethods.

Moreover, those skilled in the art will appreciate that embodiments ofthe present disclosure may be practiced with a variety ofcomputer-system configurations, including hand-held devices,multiprocessor systems, microprocessor-based or programmable-consumerelectronics, minicomputers, mainframe computers, and the like. Anynumber of computer-systems and computer networks are acceptable for usewith the present disclosure. Embodiments of the disclosure may bepracticed in distributed-computing environments where tasks areperformed by remote-processing devices that are linked through acommunications network. In a distributed-computing environment, programmodules may be located in both local and remote computer-storage mediaincluding memory storage devices. Embodiments of the present disclosuremay therefore, be implemented in connection with various hardware,software or a combination thereof in a computer system or otherprocessing system.

An illustrative methodology by which ICE design system 200 determinesthe design of an ICE core will now be described. In multivariatecalibration for spectral analysis, a regression vector r is determined,which can be combined with spectra to provide an estimate of theproperty/characteristic of interest (ŷ) as shown in Equation 1 below.Typically, ŷ (the predicted characteristic of interest) will notcompletely replicate y (the actual characteristic of interest);consequently, there will be a chemometric error (“CHE”). In Equation 1below, the rows represent the spectra (s1=spectra 1), the columns arethe wavelength channels (λ2=wavelength channel 2), and r is theregression vector (r3=the value of the regression vector for wavelengthchannel 3). ŷ is the column vector of predicted values for thecharacteristic of interest, as determined from each of the spectra.

$\begin{matrix}{{\begin{bmatrix}{s\; 1{\lambda 1}} & {s\; 1{\lambda 2}} & {s\; 1{\lambda 3}} & \ldots & {s\; 1\lambda\; x} \\{s\; 2{\lambda 1}} & {s\; 2{\lambda 2}} & {s\; 2{\lambda 3}} & \ldots & {s\; 2\lambda\mspace{11mu} x} \\{s\; 3{\lambda 1}} & {s\; 3{\lambda 2}} & {s\; 3{\lambda 3}} & \ldots & {s\; 3\lambda\; x} \\\ldots & \ldots & \ldots & \ldots & \ldots \\{{sz}\;{\lambda 1}} & {{sz}\;\lambda\; x} & {{sz}\;{\lambda 1}} & \ldots & {{sy}\;\lambda\; x}\end{bmatrix} \cdot \begin{bmatrix}r_{1} \\r_{2} \\r_{3} \\\ldots \\r_{x}\end{bmatrix}} = {\hat{y}.}} & {{Eq}.\mspace{14mu}(1)}\end{matrix}$

In multivariate optical computing (“MOC”), several components arecharacterized separately and assembled to produce the final opticalcomputing device. Because of this process, system throughput errors mayexist as a result of alignment, variations in the angles of incidence,and deviations in detectors, light sources, or other optical components.These system throughput errors are not sample spectra errors, and can bereferred to as “fixed modification” of the system throughput. The fixedmodification to the spectral throughput of the system may deterioratethe accuracy of the device in determining the sample characteristics.

This fixed modification to the spectral throughput can be called acalibration transfer error, or CTE as previously discussed. This CTE isimposed equally on each sample spectra detected by the optical computingdevice. This is represented in the left side of Equation 2 below as thevariable m, a function of wavelength (e.g., m2=CTE modification atwavelength channel 2). With this modified dataset, the originalprediction vector ŷ will be affected to instead provide other,inevitably less accurate, prediction values which are referred to hereinas the system response ŷ′.

$\begin{matrix}{{\begin{bmatrix}{s\; 1{\lambda 1}\; m\; 1} & {s\; 1{\lambda 2}\; m\; 2} & {s\; 1{\lambda 3}\; m\; 3} & \ldots & {s\; 1\lambda\;{xmx}} \\{s\; 2{\lambda 1}\; m\; 1} & {s\; 2{\lambda 2}\; m\; 2} & {s\; 2{\lambda 3}\; m\; 3} & \ldots & {s\; 2\lambda\mspace{11mu}{xmx}} \\{s\; 3{\lambda 1}\; m\; 1} & {s\; 3{\lambda 2}\; m\; 2} & {s\; 3{\lambda 3}\; m\; 3} & \ldots & {s\; 3\lambda\;{xmx}} \\\ldots & \ldots & \ldots & \ldots & \ldots \\{{sz}\;{\lambda 1}\; m\; 1} & {{sz}\;{\lambda 2}\; m\; 2} & {{sz}\;{\lambda 3}\; m\; 3} & \ldots & {{sy}\;\lambda\;{xmx}}\end{bmatrix} \cdot \begin{bmatrix}{r\; 1} \\{r\; 2} \\{r\; 3} \\\ldots \\{rx}\end{bmatrix}} = {{\hat{y}}^{\prime}.}} & {{Eq}.\mspace{14mu}(2)}\end{matrix}$

Equation 2 can be rearranged to contain a known n×p matrix and theunknown m vector. The n×p matrix in this optical computing deviceessentially contains all of the ŷ information regarding what thepredicted characteristic value should have been, were it not for the CTE(m) vector. The value ŷ′ is a measured response of the device with theunknown CTE error vector. From this Equation 2, a series of measurementsmust be made with the assembled device (with CTE) using referencesolutions that are identical to the original solutions used to make thecalibration data. Then, the actual system response to these solutionsmust be measured. Because Equation 2 is of the same form as a typicalchemometric problem, m can be solved by standard partial least squares(“PLS”) analysis as in Equation 3 below.

$\begin{matrix}{{\begin{bmatrix}{s\; 1{\lambda 1}\; r\; 1} & {s\; 1{\lambda 2}\; r\; 2} & {s\; 1{\lambda 3}\; r\; 3} & \ldots & {s\; 1\lambda\;{xrx}} \\{s\; 2{\lambda 1}\; r\; 1} & {s\; 2{\lambda 2}\; r\; 2} & {s\; 2{\lambda 3}\; r\; 3} & \ldots & {s\; 2\lambda\mspace{11mu}{xrx}} \\{s\; 3{\lambda 1}\; r\; 1} & {s\; 3{\lambda 2}\; r\; 2} & {s\; 3{\lambda 3}\; r\; 3} & \ldots & {s\; 3\lambda\;{xrx}} \\\ldots & \ldots & \ldots & \ldots & \ldots \\{{sz}\;{\lambda 1}\; r\; 1} & {{sz}\;{\lambda 2}\; r\; 2} & {{sz}\;{\lambda 3}\; r\; 3} & \ldots & {{sy}\;\lambda\;{xrx}}\end{bmatrix} \cdot \begin{bmatrix}{m\; 1} \\{m\; 2} \\{m\; 3} \\\ldots \\{mx}\end{bmatrix}} = {{\hat{y}}^{\prime}.}} & {{Eq}.\mspace{14mu}(3)}\end{matrix}$

After the CTE vector has been determined, system 200 may then use it tomodify the original regression vector to enable the original value of ŷto be recovered. This is shown in Equation 4 below, in which the n×pmatrix is actually measured containing the error, and this error can becancelled by modifying the regression vector. If any m value is zero,then the information in that wavelength channel will be lost, which mayaffect the predictability of the whole optical computing device.However, it will be noted that the expected values of m will greaterthan zero and should be close to one when there is no CTE. The bandwidthof the measurement is most important in retaining ŷ, regardless of theCTE shape; ŷ can be recovered exactly and the predictability standarderror of prediction (“SEP”) will remain the same, as long as m has nozero points. Sensitivity, however, can be affected as will be understoodby those ordinarily skilled in the art having the benefit of thisdisclosure.

$\begin{matrix}{{\begin{bmatrix}{s\; 1{\lambda 1}\; m\; 1} & {s\; 1{\lambda 2}\; m\; 2} & {s\; 1{\lambda 3}\; m\; 3} & \ldots & {s\; 1\lambda\;{xmx}} \\{s\; 2{\lambda 1}\; m\; 1} & {s\; 2{\lambda 2}\; m\; 2} & {s\; 2{\lambda 3}\; m\; 3} & \ldots & {s\; 2\lambda\mspace{11mu}{xmx}} \\{s\; 3{\lambda 1}\; m\; 1} & {s\; 3{\lambda 2}\; m\; 2} & {s\; 3{\lambda 3}\; m\; 3} & \ldots & {s\; 3\lambda\;{xmx}} \\\ldots & \ldots & \ldots & \ldots & \ldots \\{{sz}\;{\lambda 1}\; m\; 1} & {{sz}\;{\lambda 2}\; m\; 2} & {{sz}\;{\lambda 3}\; m\; 3} & \ldots & {{sy}\;\lambda\;{xmx}}\end{bmatrix} \cdot \begin{bmatrix}{r\;{1/m}\; 1} \\{r\;{2/m}\; 2} \\{r\;{3/m}\; 3} \\\ldots \\{{rx}/{mx}}\end{bmatrix}} = {\hat{y}.}} & {{Eq}.\mspace{14mu}(4)}\end{matrix}$

With the foregoing fundamental understanding, it will now be describedhow illustrative embodiments of ICE design system 200 determines thedesign of an ICE core to correct the CTE of an optical computing device.Note that the analogous calculation used in MOC varies slightly fromEquations 1-4 in that the regression vector is fixed in an ICE core. Asa result, the spectral modification m must be implemented by a spectralcorrection ICE core (i.e., CTE correcting ICE core) placed in the beampath, which will produce a spectral transmission throughput correctionon the device spectral profile. Because, with MOC, the signal istypically a ratio of the intensity with and without the ICE core, theCTE is applied to the background and ICE signals separately. As aresult, Equations 1-4 4 must be modified slightly, although theunderlying principle for determining m is the same.

To begin an illustrative analysis, ICE design system 200 may combine theraw spectral data with the device spectral throughput, as shown in FIG.3. FIG. 3 shows the original, normalized data with bandpass plottedalong the X_(axis) (wavelength (nm)) and Y_(axis) (normalizedintensity). The convolved data (spectra and system responses) isnormalized to total intensity, then a regression vector using PLS isdetermined by system 200. Applying the regression vector to theconvolved spectra will give ŷ, the expected (most accurate) predictedconcentrations. If CTE is present, ŷ contains more error than would beexpected (less accurate). The discrepancy between the expected (mostaccurate) predicted characteristic of interest and the less accuratecharacteristic of interest can then be used by system 200 to calculatethe original transfer error, as described above.

In some cases, the solution to Equation 3 can be underdetermined,depending on the number of samples available and the number ofmeasurements made. This problem may be addressed in two ways. First, forexample, if there are several analytes, several regression vectors maybe made available (for MOC, this corresponds to an optical computingdevice with several ICE cores). The samples plotted in FIG. 3 containsfour analytes: water, NaOH, Na₂CO₃, and NaCl. Using these fourregression vectors combined with the 34 sets of spectral data shown inFIG. 3 enables 132 combinations on which to calculate the CTE. In MOC,four sets of ŷ′ can be measured if four ICE cores are designed, thusincreasing the amount of data with which to determine the CTE.Alternatively, the second method of determining CTE in underdeterminedsystems is to reduce the resolution of m, and thus the number ofparameters to fit. An example is to use a Fourier transforminterpolation function to change the resolution of m.

FIG. 4 provides two examples of simulated CTE profiles (shown by lines Aand B), and the back-calculated versions of the function (shown by linesC and D) that are based on a Fourier transform interpolation of eightpoints, all generated using ICE design system 200. Line E indicates thestandard deviation (“SD”) of the spectral data from FIG. 3 and shows thewavelengths in which the sample does not transmit (SD values of nearzero). With the back-calculated CTE profiles, it is evident that in theregions in which there is no transmission, the CTE is more poorlyrecreated; in the regions in which the SD is high, the CTE Is quiteclosely replicated. Line A illustrates the first function replicated;the slight curve of this function reflects the type of CTE expected. Itis replicated well when the SD of the raw data is significantly abovezero. The second CTE function has a sharp transit. Although it is notidentical to the original CTE and is rather unrealistic, it is stillreasonably replicated and can compensate very well for the predictionerror. The slopes and curves are back-calculated well using this method;predictabilities are compensated well, even when deviations exist fromthe original CTE.

Accordingly, in certain illustrative embodiments of the presentdisclosure, ICE design system 200 utilizes the foregoing methodology todesign an ICE core to compensate for the CTE. The resulting ICE core(s)are design to have the appropriate spectral profile to produces an mvalue that corrects ŷ′ back to ŷ, or alternative embodiments, closer tothe actual values, y, where y′>ŷ>y. To achieve this in one embodiment,ICE design system 200 defines m as the transmission profile of anoptical filter (i.e., ICE core), constrained as it is with one or morethin film layers with the possibility to vary the layer thicknesses (asdiscussed above in relation to FIG. 1). The thickness of layer(s) 102,and layer(s) 104 are then adjusted to produce a correction profile, m,that results in a spectral profile throughput modification that providesa greater accuracy level for the predicted characteristic of interest.In other words, system 200 designs an ICE core that applies acalibration transfer error correction, or CTE correction, to the outputof the optical computing device.

FIG. 5 is a block diagram of an illustrative architecture of an opticalcomputing device 500 employing a transmission mode design, which may beutilized in one or more of the optical computing devices of the presentdisclosure. As will be described, optical computing device 500 correctsthe CTE optically using an ICE core. An electromagnetic radiation source508 may be configured to emit or otherwise generate electromagneticradiation 510. As understood in the art, electromagnetic radiationsource 508 may be any device capable of emitting or generatingelectromagnetic radiation. For example, electromagnetic radiation source508 may be a light bulb, light emitting device, laser, blackbody,photonic crystal, or X-Ray source, natural luminescence, etc. In oneembodiment, electromagnetic radiation 510 may be configured to opticallyinteract with the sample 506 to thereby generate sample-interacted light512. Sample 506 may be any desired sample, such as, for example, a fluid(liquid or gas), solid substance or material such as, for example,hydrocarbons or food products. While FIG. 5 shows electromagneticradiation 510 as passing through or incident upon the sample 506 toproduce sample-interacted light 512 (i.e., transmission or fluorescentmode), it is also contemplated herein to reflect electromagneticradiation 510 off of the sample 506 (i.e., reflectance mode), such as inthe case of a sample 506 that is translucent, opaque, or solid, andequally generate the sample-interacted light 512.

After being illuminated with electromagnetic radiation 510, sample 506containing an analyte of interest (a characteristic of the sample)produces an output of electromagnetic radiation (sample-interacted light512, for example). As previously described, sample-interacted light 512also contains spectral information of the sample used to determine oneor more characteristics of sample 506. Although not specifically shown,one or more spectral elements may be employed in optical computingdevice 500 in order to restrict the optical wavelengths and/orbandwidths of the system and, thereby, eliminate unwantedelectromagnetic radiation existing in wavelength regions that have noimportance. As will be understood by those ordinarily skilled in the arthaving the benefit of this disclosure, such spectral elements can belocated anywhere along the optical train, but are typically employeddirectly after the light source which provides the initialelectromagnetic radiation.

Although not shown, optical computing device 500 may be coupled to aremote power supply, while in other embodiments optical computing device500 comprises an on-board battery. Optical computing device 500 may alsocomprise a signal processor (not shown), communications module (notshown) and other circuitry necessary to achieve the objectives of thepresent disclosure, as will be understood by those ordinarily skilled inthe art having the benefit of this disclosure. It will also berecognized that the software instructions necessary to carry out theobjectives of the present disclosure may be stored within storagelocated on optical computing device 500 or loaded into that storage froma CD-ROM or other appropriate storage media via wired or wirelessmethods.

Alternatively, however, the processor may be located remotely fromoptical computing device 500. In such embodiments, a communications linkprovides a medium of communication between the processor and opticalcomputing device 500. The communications link may be a wired link, suchas, for example, a fiber optic cable. Alternatively, however, the linkmay be a wireless link. In certain illustrative embodiments, the signalprocessor controls operation of optical computing device 500. Opticalcomputing device 500 may also include a transmitter and receiver(transceiver, for example) (not shown) that allows bi-directionalcommunication over a communications link in real-time. In certainillustrative embodiments, optical computing device 500 will transmit allor a portion of the sample characteristic data to a remote processor forfurther analysis. However, in other embodiments, such analysis iscompletely handled by optical computing device 500 and the resultingdata is then transmitted remotely for storage or subsequent analysis. Ineither embodiment, the processor handling the computations may, forexample, analyze the characteristic data, or perform simulations basedupon the characteristic data, as will be readily understood by thoseordinarily skilled in the art having the benefit of this disclosure.

Still referring to the illustrative embodiment of FIG. 5,sample-interacted light 512 is then directed to a first ICE core 504 a,which has been designed to be associated with a particularcharacteristic of sample 506 or may be designed to approximate or mimicthe regression vector of the characteristic in a desired manner, aswould be understood by those ordinarily skilled in the art having thebenefit of this disclosure. Additionally, however, optical computingdevice 500 also includes a second ICE core 504 b which is designed tocorrect the CTE, as previously described. Second ICE core 504 b ispositioned in series with first ICE core 504 a. Also, as previouslydescribed, ICE cores 504 a and 504 b have different spectral profilesand, as a result, second ICE core 504 b itself corrects the CTE presentin optical computing device 500.

When sample-interacted light 512 optically interacts with first ICE core504 a, a first electromagnetic beam 514 a is generated which, aspreviously described, may contain the less accurate device response 9′.First electromagnetic beam 514 a then optically interacts with secondICE core 504 b to thereby produce second electromagnetic beam 514 b.Since second ICE core 504 b contains the appropriate spectral profilethat produces the m value, ŷ′ is corrected back to ŷ, closer to theactual values, y, where y′>ŷ>y, thus providing a CTE correction to thebeam. Thereafter, second electromagnetic beam 514 b, which is nowcorrectly related to the characteristic or analyte of interest, isconveyed to a series detector 516 for analysis and quantification. Note,however, that in an alternative embodiment, the CTE correcting ICE coremay be ICE core 504 a, while ICE core 504 b would include theconventional design.

Detector 516 may be any device capable of detecting electromagneticradiation, and may be generally characterized as an optical transducer.For example, detector 516 may be, but is not limited to, a thermaldetector such as a thermopile or photoacoustic detector, a semiconductordetector, a piezo-electric detector, charge coupled device detector,video or array detector, split detector, photon detector (such as aphotomultiplier tube), photodiodes, local or distributed optical fibers,and/or combinations thereof, or the like, or other detectors known tothose ordinarily skilled in the art. Detector 516 is further configuredto produce an output signal 528 in the form of a voltage thatcorresponds to the characteristic of the sample 506. In at least oneembodiment, output signal 528 produced by detector 516 and thecharacteristic concentration of the sample 506 may be directlyproportional. In other embodiments, the relationship may be a polynomialfunction, an exponential function, and/or a logarithmic function.

Although not shown, optical computing device 500 may include a seconddetector arranged to receive and detect electromagnetic radiation(sample-interacted light 512) and output a normalizing signal, asunderstood in the art. Here, reflected electromagnetic radiation mayinclude a variety of radiating deviations stemming from electromagneticradiation source 508 such as, for example, intensity fluctuations in theelectromagnetic radiation, interferent fluctuations (for example, dustor other interferents passing in front of the electromagnetic radiationsource), combinations thereof, or the like. Thus, the second detectordetects such radiating deviations as well.

Although not shown in FIG. 5, in certain illustrative embodiments,detector 516 may be communicably coupled to a signal processor (notshown) on-board optical computing device 500 such that a normalizingsignal indicative of electromagnetic radiating deviations may beprovided or otherwise conveyed thereto. The signal processor may then beconfigured to computationally combine the normalizing signal with outputsignal 528 to provide a more accurate determination of thecharacteristic of sample 506. However, in other embodiments thatutilized only one detector as shown, the signal processor would becoupled to the one detector. Nevertheless, in the embodiment of FIG. 5,for example, the signal processor may utilize multivariate analysistechniques such as, for example, standard partial least squares (“PLS”)which are available in most statistical analysis software packages (forexample, XL Stat for MICROSOFT® EXCEL® the UNSCRAMBLER® from CAMOSoftware and MATLAB® from MATHWORKS®), as will be understood by thoseordinarily skilled in the art having the benefit of this disclosure.Thereafter, the resulting data is then transmitted to the processor forfurther operations.

FIG. 6 is a block diagram of an illustrative architecture of an opticalcomputing device 600 utilizing a CTE error correction circuit, accordingto certain illustrative embodiments of the present disclosure. As willbe described, optical computing device 600 corrects the CTEelectronically using the correction circuit. An electromagneticradiation source 608 generates electromagnetic radiation 610, which isthen split into two beams 610 a and 610 b using beam splitters and/orreflectors 609 a and 609 b, as understood in the art. Electromagneticradiation beams 610 a,b then optically interact with sample 606 toproduce sample-interacted light 612 a,b, respectively. A first ICE core604 a and a second ICE core 604 b are positioned in parallelconfiguration to receive sample-interacted light 612 a,b, respectively,and thereby produce first electromagnetic beam 614 a and secondelectromagnetic beam 614 b. In this example, second ICE core 604 bserves as the CTE correcting ICE core; however, in alternateembodiments, first ICE core 604 a may serve as the CTE correcting ICEcore as previously described.

A first detector 616 is positioned in series with first ICE core 604 ato thereby optically interact with first electromagnetic beam 614 a toproduce first signal 628 which corresponds to a desired characteristicof sample 606. A second detector 618 is positioned in series with secondICE core 604 b to optically interact with second electromagnetic beam614 b which contains the transmission function necessary to produce thecorrecting m value. This interaction results in the production of secondsignal 628 b.

Both the first and second signals 628 a,b are utilized to determine thecharacteristic of sample 606, as one of the signals (in this example,second sign 628 b) is used to apply a CTE correction to the othersignal. In this illustrative embodiment, a CTE correction circuit 630applies the CTE correction of second signal 628 b to first signal 628 a.There are a variety of ways in which to design circuit 630. For example,circuit 630 may be a differential op-amp circuit coupled to detectors616 and 618 to thereby subtract signal 628 b from signal 628 a.Alternatively, however, other math operators may be design into circuit630, as would be understood by those ordinarily skilled in the arthaving the benefit of this disclosure. Nevertheless, the resultingoutput signal 632 corresponds to the CTE corrected characteristic, andis ultimately processed accordingly by a remote or locate processor (notshown).

In an alternate embodiment of optical computing device 600, a computerprocessor (not shown) may be utilized instead of CTE correction circuit630. In such an embodiment, correction of the CTE (using signals 628a,b) would be performed by the computer processor via softwareinstructions. For example, the software instructions would enable thecomputer processor to subtract second signal 628 b from first signal 628a to thereby determine the CTE corrected characteristic of sample 606.

In yet another alternative embodiment, the conventional ICE core and theCTE corrective ICE core may be one monolithic device. For example, oneof the ICE cores may be deposited onto (or attached to) one side of asubstrate, while the other ICE core is attached to, or deposited onto),the opposite side of the substrate. Such an alteration would be apparentto one ordinarily skilled in the art having the benefit of thisdisclosure.

Those same ordinarily skilled persons will realize the aforementionedoptical computing devices are illustrative in nature, and that there area variety of other optical configurations which may be utilized. Theseoptical configurations not only include the reflection, absorption ortransmission methods described herein, but can also involve scattering(Raleigh & Raman, for example) as well as emission (fluorescence, X-rayexcitation, etc., for example). The foregoing optical computing devicesmay be implemented in a variety of ways, including, for example, in adownhole environment, compact device, hand-held devices or otherportable devices.

Accordingly, the illustrative embodiments of the present disclosureprovide for the design and fabrication of ICE cores that can compensatefor the error in an assembled optical computing device's spectralprofile. As a result, the integrity of the optical device's performanceis maintained even when unaccounted-for errors in the modeling processare present. As a result, there is no need to recollect spectral data inorder to compensate for the errors.

Embodiments described herein further relate to any one or more of thefollowing paragraphs:

1. An optical computing device, comprising electromagnetic radiationthat optically interacts with a sample to produce sample-interactedlight; a first Integrated Computational Element (“ICE”) core; a secondICE core positioned in series with the first ICE core; and a detectorpositioned in series with the first and second ICE cores to receive anelectromagnetic beam which has passed through the first and second ICEcores, the detector thereby generates a signal utilized to determine acharacteristic of the sample.

2. An optical computing device as defined in paragraph 1, wherein thefirst and second ICE cores have different spectral profiles.

3. An optical computing device as defined in any of paragraphs 1-2,wherein the first or second ICE cores are positioned to apply acalibration transfer error correction to the electromagnetic beam.

4. An optical computing device as defined in any of paragraphs 1-3,wherein the calibration transfer error correction is determined basedupon components of the optical computing device.

5. An optical computing device, comprising electromagnetic radiationthat optically interacts with a sample to produce sample-interactedlight; a first Integrated Computational Element (“ICE”) core positionedto optically interact with the sample-interacted light to therebygenerate a first electromagnetic beam which corresponds to acharacteristic of the sample; a second ICE core positioned in parallelwith the first ICE core to optically interact with the sample-interactedlight to thereby generate a second electromagnetic beam which alsocorresponds to the characteristic of the sample; and a first detectorpositioned in series with the first ICE core to receive the firstelectromagnetic beam and thereby generate a first signal utilized todetermine the characteristic of the sample; and a second detectorpositioned in series with the second ICE core to receive the secondelectromagnetic beam and thereby generate a second signal utilized todetermine the characteristic of the sample, wherein one of the first orsecond signals is utilized to apply a calibration transfer errorcorrection to the other signal.

6. An optical computing device as defined in paragraph 5, wherein thefirst and second ICE cores have different spectral profiles.

7. An optical computing device as defined in any of paragraphs 5-6,wherein the calibration transfer error correction is determined basedupon components of the optical computing device.

8. An optical computing device as defined in any of paragraphs 5-7,further comprising a correction circuit positioned to receive the firstand second signals, and thereby utilize one of the first or secondsignals to apply the calibration transfer error correction to the othersignal.

9. An optical computing device as defined in any of paragraphs 5-8,further comprising a computer processor positioned to receive the firstand second signals, and thereby utilize one of the first or secondsignals to apply the calibration transfer error correction to the othersignal.

10. A method utilizing an optical computing device, comprising opticallyinteracting electromagnetic radiation with a sample to producesample-interacted light; optically interacting the sample-interactedlight with a first Integrated Computational Element (“ICE”) core toproduce a first electromagnetic beam; optically interacting the firstelectromagnetic beam with a second ICE core positioned in series withthe first ICE core to thereby produce a second electromagnetic beam;optically interacting the second electromagnetic beam with a detectorpositioned in series with the first and second ICE cores to therebygenerate a signal; and utilizing the signal to determine acharacteristic of the sample.

11. A method as defined in paragraph 10, wherein the first and secondICE cores have different spectral profiles.

12. A method as defined in any of paragraphs 10-11, further comprisingutilizing the first or second ICE cores to apply a calibration transfererror correction to the second electromagnetic beam.

13. A method as defined in any of paragraphs 10-12, wherein thecalibration transfer error correction is achieved using the methodcomprising calculating a calibration transfer error for the opticalcomputing device based on components of the optical computing device;and utilizing the calibration transfer error to design the first orsecond ICE cores to correct for the calibration transfer error, thusresulting in the calibration transfer error correction.

14. A method utilizing an optical computing device, comprising opticallyinteracting electromagnetic radiation with a sample to producesample-interacted light; optically interacting the sample-interactedlight with a first Integrated Computational Element (“ICE”) core tothereby generate a first electromagnetic beam; optically interacting thesample-interacted light with a second ICE core to thereby generate asecond electromagnetic beam; optically interacting the firstelectromagnetic beam with a first detector to thereby generate a firstsignal; optically interacting the second electromagnetic beam with asecond detector to thereby generate a second signal; utilizing one ofthe first or second signals to apply a calibration transfer errorcorrection to the other signal; and utilizing the first and secondsignals to determine a characteristic of the sample.

15. A method as defined in paragraph 14, wherein the first and secondICE cores have different spectral profiles.

16. A method as defined in any of paragraphs 14-15, wherein thecalibration transfer error correction is achieved using the methodcomprising calculating a calibration transfer error for the opticalcomputing device based on components of the optical computing device;and utilizing the calibration transfer error to design the first orsecond ICE cores to produce an electromagnetic beam used to correct forthe calibration transfer error, thus resulting in the calibrationtransfer error correction.

17. A method as defined in any of paragraphs 14-16, wherein utilizingone of the first or second signals to apply the calibration transfererror correction to the other signal comprises transmitting the firstand second signals to a correction circuit; and utilizing the correctioncircuit to apply the calibration transfer error correction to the othersignal.

18. A method as defined in any of paragraphs 14-17, wherein utilizingone of the first or second signals to apply the calibration transfererror correction to the other signal comprises transmitting the firstand second signals to a computer processor; and utilizing the computerprocessor to apply the calibration transfer error correction to theother signal.

19. An optical computing method, comprising calculating a calibrationtransfer error for an optical computing device based on components ofthe optical computing device; utilizing the calibration transfer errorto determine a calibration transfer error correction; and utilizing thecalibration transfer error correction to generate a signal in theoptical computing device which corresponds to a characteristic of asample being analyzed by the optical computing device.

20. A method as defined in paragraph 19, wherein utilizing thecalibration transfer error correction to generate the signal comprisesproviding a first and second Integrated Computational Element (“ICE”)core in the optical computing device; and utilizing one of the ICE coresto apply the calibration transfer error correction.

21. A method as defined in any of paragraphs 19-20, wherein utilizingthe calibration transfer error correction to generate the signalcomprises applying the calibration transfer error correction using acorrection circuit.

22. A method as defined in any of paragraphs 19-21, wherein utilizingthe calibration transfer error correction to generate the signalcomprises applying the calibration transfer error correction using acomputer processor.

23. A method to fabricate an optical computing device, comprisingcalculating a calibration transfer error for an optical computing devicebased on components of the optical computing device; utilizing thecalibration transfer error to determine an optical spectral profilenecessary to correct for the calibration transfer error; and designing afirst Integrated Computational Element (“ICE”) core which corresponds toa characteristic of a sample being analyzed by the optical computingdevice.

24. A method as defined in paragraph 23, further comprising positioningthe first ICE core in series with a second ICE core such that the firstICE core corrects the calibration transfer error present within anoutput beam of the second ICE core.

25. A method as defined in any of paragraphs 23-24, further comprisingpositioning the first ICE core in parallel with a second ICE core;positioning a first detector in series with the first ICE core; andpositioning a second detector in series with the second ICE core,wherein an output signal of the first detector is utilized to correctfor the calibration transfer error present within an output signal ofthe second detector.

26. A method as defined in any of paragraphs 23-25, further comprisingpositioning a correction circuit in series with the first and seconddetectors to thereby correct the calibration transfer error using theoutput signal of the first detector.

27. A method as defined in any of paragraphs 23-26, further comprisingpositioning a computer processor in series with the first and seconddetectors to thereby correct the calibration transfer error using theoutput signal of the first detector.

Although various embodiments and methodologies have been shown anddescribed, the disclosure is not limited to such embodiments andmethodologies and will be understood to include all modifications andvariations as would be apparent to one skilled in the art. Therefore, itshould be understood that the disclosure is not intended to be limitedto the particular forms disclosed. Rather, the intention is to cover allmodifications, equivalents and alternatives falling within the spiritand scope of the disclosure as defined by the appended claims.

What is claimed is:
 1. An optical computing device, comprising:electromagnetic radiation that optically interacts with a sample toproduce sample-interacted light; a first Integrated ComputationalElement (“ICE”) core; a second ICE core positioned in series with thefirst ICE core; and a detector positioned in series with the first andsecond ICE cores to receive an electromagnetic beam which has passedthrough the first and second ICE cores, the detector thereby generates asignal utilized to determine a characteristic of the sample, wherein thefirst or second ICE core is positioned to apply a calibration transfererror correction to the electromagnetic beam.
 2. An optical computingdevice as defined in claim 1, wherein the first and second ICE coreshave different spectral profiles.
 3. An optical computing device asdefined in claim 1, wherein the calibration transfer error correction isdetermined based upon components of the optical computing device.
 4. Anoptical computing device, comprising: electromagnetic radiation thatoptically interacts with a sample to produce sample-interacted light; afirst Integrated Computational Element (“ICE”) core positioned tooptically interact with the sample-interacted light to thereby generatea first electromagnetic beam which corresponds to a characteristic ofthe sample; a second ICE core positioned in parallel with the first ICEcore to optically interact with the sample-interacted light to therebygenerate a second electromagnetic beam which also corresponds to thecharacteristic of the sample; a first detector positioned in series withthe first ICE core to receive the first electromagnetic beam and therebygenerate a first signal utilized to determine the characteristic of thesample; and a second detector positioned in series with the second ICEcore to receive the second electromagnetic beam and thereby generate asecond signal utilized to determine the characteristic of the sample,wherein one of the first or second signals is utilized to apply acalibration transfer error correction to the other signal.
 5. An opticalcomputing device as defined in claim 4, wherein the first and second ICEcores have different spectral profiles.
 6. An optical computing deviceas defined in claim 4, wherein the calibration transfer error correctionis determined based upon components of the optical computing device. 7.An optical computing device as defined in claim 4, further comprising acorrection circuit positioned to receive the first and second signals,and thereby utilize one of the first or second signals to apply thecalibration transfer error correction to the other signal.
 8. An opticalcomputing device as defined in claim 4, further comprising a computerprocessor positioned to receive the first and second signals, andthereby utilize one of the first or second signals to apply thecalibration transfer error correction to the other signal.
 9. A methodutilizing an optical computing device, comprising: optically interactingelectromagnetic radiation with a sample to produce sample-interactedlight; optically interacting the sample-interacted light with a firstIntegrated Computational Element (“ICE”) core to produce a firstelectromagnetic beam; optically interacting the first electromagneticbeam with a second ICE core positioned in series with the first ICE coreto thereby produce a second electromagnetic beam; utilizing the first orsecond ICE core to apply a calibration transfer error correction to thesecond electromagnetic beam; optically interacting the secondelectromagnetic beam with a detector positioned in series with the firstand second ICE cores to thereby generate a signal; and utilizing thesignal to determine a characteristic of the sample.
 10. A method asdefined in claim 9, wherein the first and second ICE cores havedifferent spectral profiles.
 11. A method as defined in claim 9, whereinthe calibration transfer error correction is achieved using the methodcomprising: calculating a calibration transfer error for the opticalcomputing device based on components of the optical computing device;and utilizing the calibration transfer error to design the first orsecond ICE cores to correct for the calibration transfer error, thusresulting in the calibration transfer error correction.
 12. A methodutilizing an optical computing device, comprising: optically interactingelectromagnetic radiation with a sample to produce sample-interactedlight; optically interacting the sample-interacted light with a firstIntegrated Computational Element (“ICE”) core to thereby generate afirst electromagnetic beam; optically interacting the sample-interactedlight with a second ICE core to thereby generate a secondelectromagnetic beam; optically interacting the first electromagneticbeam with a first detector to thereby generate a first signal; opticallyinteracting the second electromagnetic beam with a second detector tothereby generate a second signal; utilizing one of the first or secondsignals to apply a calibration transfer error correction to the othersignal; and utilizing the first and second signals to determine acharacteristic of the sample.
 13. A method as defined in claim 12,wherein the first and second ICE cores have different spectral profiles.14. A method as defined in claim 12, wherein the calibration transfererror correction is achieved using the method comprising: calculating acalibration transfer error for the optical computing device based oncomponents of the optical computing device; and utilizing thecalibration transfer error to design the first or second ICE cores toproduce an electromagnetic beam used to correct for the calibrationtransfer error, thus resulting in the calibration transfer errorcorrection.
 15. A method as defined in claim 12, wherein utilizing oneof the first or second signals to apply the calibration transfer errorcorrection to the other signal comprises: transmitting the first andsecond signals to a correction circuit; and utilizing the correctioncircuit to apply the calibration transfer error correction to the othersignal.
 16. A method as defined in claim 12, wherein utilizing one ofthe first or second signals to apply the calibration transfer errorcorrection to the other signal comprises: transmitting the first andsecond signals to a computer processor; and utilizing the computerprocessor to apply the calibration transfer error correction to theother signal.
 17. An optical computing method, comprising: calculating acalibration transfer error for an optical computing device based oncomponents of the optical computing device; utilizing the calibrationtransfer error to determine a calibration transfer error correction; andutilizing a first or second Integrated Computational Element (“ICE”)core of the optical computing device to apply the calibration transfererror correction, thereby generating a signal in the optical computingdevice which corresponds to a characteristic of a sample being analyzedby the optical computing device.
 18. A method as defined in claim 17,wherein applying the calibration transfer error correction furthercomprises applying the calibration transfer error correction using acorrection circuit.
 19. A method as defined in claim 17, whereinapplying the calibration transfer error correction further comprisesapplying the calibration transfer error correction using a computerprocessor.
 20. A method to fabricate an optical computing device,comprising: calculating a calibration transfer error for an opticalcomputing device based on components of the optical computing device;utilizing the calibration transfer error to determine an opticalspectral profile necessary to correct for the calibration transfererror; and designing a first Integrated Computational Element (“ICE”)core which corresponds to a characteristic of a sample being analyzed bythe optical computing device.
 21. A method as defined in claim 20,further comprising positioning the first ICE core in series with asecond ICE core such that the first ICE core corrects the calibrationtransfer error present within an output beam of the second ICE core. 22.A method as defined in claim 20, further comprising: positioning thefirst ICE core in parallel with a second ICE core; positioning a firstdetector in series with the first ICE core; and positioning a seconddetector in series with the second ICE core, wherein an output signal ofthe first detector is utilized to correct for the calibration transfererror present within an output signal of the second detector.
 23. Amethod as defined in claim 22, further comprising positioning acorrection circuit in series with the first and second detectors tothereby correct the calibration transfer error using the output signalof the first detector.
 24. A method as defined in claim 22, furthercomprising positioning a computer processor in series with the first andsecond detectors to thereby correct the calibration transfer error usingthe output signal of the first detector.